Skin dysbiosis and loss of microbiome site specificity in critically ill patients

ABSTRACT An increasing amount of evidence has linked critical illness with dysbiotic microbiome signatures in different body sites. The disturbance of the indigenous microbiota structures has been further associated with disease severity and outcome and has been suggested to pose an additional risk for complications in intensive care units (ICUs), including hospital-acquired infections. A better understanding of the microbial dysbiosis in critical illness might thus help to develop strategies for the prevention of such complications. While most of the studies addressing microbiome changes in ICU patients have focused on the gut, the lung, or the oral cavity, little is known about the microbial communities on the skin of ICU patients. Since the skin is the outermost organ and the first immune barrier against pathogens, its microbiome might play an important role in the risk management for critically ill patients. This observational study characterizes the skin microbiome in ICU patients covering five different body sites at the time of admission. Our results show a profound dysbiosis on the skin of critically ill patients, which is characterized by a loss of site specificity and an overrepresentation of gut bacteria on all skin sites when compared to a healthy group. This study opens a new avenue for further investigations on the effect of skin dysbiosis in the ICU setting and points out the need of strategies for the management of dysbiosis in critically ill patients. IMPORTANCE Unbalanced gut microbiota in critically ill patients has been associated with poor outcome and complications during the intensive care unit (ICU) stay. Whether the disturbance of the microbial communities in these patients is extensive for other body sites, such as the skin, is largely unknown. The skin not only is the largest organ of the body but also serves as the first immune barrier against potential pathogens. This study characterized the skin microbiota on five different body sites in ICU patients at the time of admission. The observed disturbance of the bacterial communities might help to develop new strategies in the risk management of critically ill patients.


SUPPLEMENTARY MATERIAL (DETAILED METHODS) Study design and sampling
This observational study aimed to characterize the skin microbiome in ICU-patients covering five different body sites: the axillary vault (AV), the gluteal crease (GC), the hypothenar palm (HP), the nares (N) and the external auditory canal (EAC).These sites were selected in order to obtain a good representation of different microbial communities in dry, moist and sebaceous microenvironments.
An overview of the study design is provided in Suppl.Fig. S1.Twenty-six ICU-patients (age range 25-90y; η = 62.5y) from 3 different hospitals (7 patients from Charité -Universitätsmedizin Berlin, 9 patients from Jena University Hospital, and 10 patients from the Thüringen-Kliniken Gregorius Agricola in Saalfeld).Any patient with an anticipated ICU-stay of more than 5 days was eligible for this study and sampling was performed by trained personnel within the first 12 hours after ICU admission.
Twenty-seven healthy volunteers (age range 20-61y; η = 35 y) not receiving antimicrobial therapy within the last 6 months served as a control group.Informed consent was obtained for all participating individuals in accordance with the Declaration of Helsinki and the Ethics Committees of Charité -Universitätsmedizin Berlin (ID: EA1/1093/16).This study was conducted within a cluster randomized controlled trial (cRCT) that was registered at the German Register for Clinical Studies (Deutsches Register für Klinische Studien, DRKS00010475).In all cases, sampling was performed by swabbing.The sterile swabs used for skin sampling were premoistened in PBS buffer before the samples were taken.
After sampling, each swab was stubbed out in a labeled 1.5 ml Eppendorf-tube prefilled with 300 µl PBS, and immediately stored at -80°C until further use.The PBS tube used for premoistening was used as blank control and subjected to simultaneous sample processing with all other samples from each sampling event.

DNA extraction
DNA isolation was performed using the ZymoBIOMICS DNA Miniprep Kit (Zymo Research) with some additional modifications of the manufacturer's lysis step in order to increase the DNA yield and the coverage of gram positive bacteria.In short: the sample (≈ 250 µl) was transferred to a ZR Bashing-Bead Lysis Tube in addition to 750 µl Lysis Solution and homogenized in SpeedMill Plus (Analytik Jena) using a 5-minute program at maximum speed.Binding and washing steps were performed according to manufacturer's instructions.The elution step was performed with 50 µl of pre-heated (60°C) DNase/RNase free water, and repeated twice.

Library construction and 16S rRNA gene amplicon sequencing
Amplicon libraries and sequencing was performed as described previously (1, 2) and following the guidelines implemented by Caporaso and Walters et al (3,4).In short.F515-fusion primers with Golaybarcodes and the R806-constructs were used as detailed in Supplementary table S1.The 50 μl PCR reaction was set up on a CAS-1200 pipetting robot (Qiagen) and carried out on a Thermal Cycler S1000 (BioRad) using the Platinum PCR SuperMix (Thermo Fisher Scientific).Thermal conditions included an initial denaturation step (94°C, 3min), 35 amplification cycles (94°C, 15s; 58°C, 20s; 72°C, 30s) and an elongation step at 72°C for 10min.The resulting PCR products were quantified on D1000 Tapes using a TapeStation 2200 (Agilent Technologies), equimolarly pooled and finally purified by size-selection on a 2% SizeSelect E-Gels (Thermo Fisher Scientific).The final libraries were prepared for Illumina sequencing using the MiSeq Reagent Kit v2 (Illumina) following manufacturer's instructions.The sequencing reagents and the run plan were adapted as described by Caporaso and colleagues (3).To account for low diversity read outcomes, the library was spiked with 20% PhiX library (Illumina) and the cluster density kept at 600-800 K/mm 2 .Sequencing was performed on an Illumina MiSeq apparatus with 251 cycles.

Sequencing Data Analysis
Raw reads were demultiplexed in QIIME 2 (5) (https://qiime2.org).After quality assessment the q2-dada2 plugin was used to denoise, filter out chimeric sequences and singletons, join pair-end sequences and dereplicate final high quality sequences (6).For each sample we obtained a minimum of 5000 reads, with a mean sequencing depth of 103692 reads per sample (after passing quality filter).
Additional run statistics are detailed in suppl.Table S2.Unless otherwise stated, we used default parameters for all DADA2 functions.Taxonomy assignment of the dada2-output feature table was performed using a pre-trained Naive Bayes classifier.This was trained on the SILVA REF NR 99 database (release 132) and sequences were extracted using the 515F forward (GTGYCAGCMGCCGCGGTAA) and 806R reverse primer (GGACTACNVGGGTWTCTAAT) matching the v4 region of the bacterial 16S rRNA gene (7).Taxonomic classification was performed using the sub-classifying genus option implemented in the SILVA database, which avoids loss of data and allows for differentiation between different bacterial strains within a same genus.Sub-classified genus results in unspecified taxa which is assigned a number.The datasets generated in this study are available at the SRA database under the following Bioproject accession number: PRJNA909975 [https://www.ncbi.nlm.nih.gov/sra/PRJNA909975].Suppl.Figure S2.-Taxonomic summary with the relative distributions of the microbial communities analyzed separately for each skin site.Shown are the relative abundances of the 25 most important taxa for each individual of the two analyzed cohort (left panel: healthy volunteers vs ICU-patients, ordered by the abundance of the dominant genus), as well as the collapsed mean values for the taxonomies of each group (right panel).